Large language model based framework for automated extraction of genetic interactions from unstructured data.

Extracting biological interactions from published literature helps us understand complex biological systems, accelerate research, and support decision-making in drug or treatment development. Despite efforts to automate the extraction of biological relations using text mining tools and machine learning pipelines, manual curation continues to serve as the gold standard. However, the rapidly increasing volume of literature pertaining to biological relations poses challenges in its manual curation and refinement. These challenges are further compounded because only a small fraction of the published literature is relevant to biological relation extraction, and the embedded sentences of relevant sections have complex structures, which can lead to incorrect inference of relationships. To overcome these challenges, we propose GIX, an automated and robust Gene Interaction Extraction framework, based on pre-trained Large Language models fine-tuned through extensive evaluations on various gene/protein interaction corpora including LLL and RegulonDB. GIX identifies relevant publications with minimal keywords, optimises sentence selection to reduce computational overhead, simplifies sentence structure while preserving meaning, and provides a confidence factor indicating the reliability of extracted relations. GIX's Stage-2 relation extraction method performed well on benchmark protein/gene interaction datasets, assessed using 10-fold cross-validation, surpassing state-of-the-art approaches. We demonstrated that the proposed method, although fully automated, performs as well as manual relation extraction, with enhanced robustness. We also observed GIX's capability to augment existing datasets with new sentences, incorporating newly discovered biological terms and processes. Further, we demonstrated GIX's real-world applicability in inferring E. coli gene circuits.

Combining kinetic orders for efficient S-System modelling of gene regulatory network.

S-System models, non-linear differential equation models, are widely used for reconstructing gene regulatory networks from temporal gene expression data. An S-System model involves two states, generation and degeneration, and uses the kinetic parameters gij and hij, to represent the direction, nature, and intensity of the genetic interactions. The need for learning a large number of model parameters results in increased computational expense. Previously, we improved the performance of the algorithm using dynamic allocation of the maximum in-degree for each gene. While the method was effective for smaller networks, a large amount of computation was still needed for larger networks. This problem arose mainly due to the increased occurrence of invalid networks during optimization, primarily because the two kinetic parameters (gij and hij) of the S-System model converge independently during optimization. Being independent, these two parameters can converge to values that can indicate contradictory gene interactions, specifically inhibition or activation. In this study, to address this major challenge in S-System modelling, we developed a novel method that includes two features: a penalty term that penalizes those networks with invalid kinetic orders, and a parameter, wij, derived by combining the kinetic parameters gij and hij. The novel penalty term was used for candidate selection during the process of optimizing the DRNI (Dynamically Regulated Network Initialization) algorithm. Rather than remaining constant, it is dynamic, with its magnitude dependent on the number of invalid interactions in the given network. This approach encourages the generation of valid candidate solutions, and eliminates invalid networks in a systematic manner. The previous DRNI method, a two-stage approach which uses dynamic allocation of the maximum in-degree for each gene, was further improved by adding a third stage which applies the proposed wij to handle the invalid regulations that may still exist in that candidate solutions. The method was tested on different gene expression datasets, and was able to reduce the number of iterations and produce improved network accuracies. For a 20 gene network, the number of generations required for convergence was reduced by 300, and the F-score improved by 0.05 compared to our previously reported DRNI approach. For the well-known 10 gene networks of the DREAM challenge, our method produced an improvement in the average area under the ROC curve of the DREAM4 10 gene networks.

Impact of inflammatory bowel disease on student experience in postsecondary education.

Objectives: This literature review seeks to identify based on the current literature how the burden of disease for IBD patients manifests itself as this cohort transitions simultaneously from pediatric to adult care and from secondary to post-secondary education. Methods: This paper reviews the current literature regarding postsecondary students with IBD and provides a summary of research regarding key factors in their quality of experience. The research was conducted through databases including Taylor & Francis, PubMed, as well as searches via Google Scholar. Results: Over the course of this search, thirty-three relevant studies were identified. These studies addressed the themes outlined in this paper, including academic performance, social adaptation, transition of care, as well as overall transition to a postsecondary institution. Each of these is further broken down to identify specific determinants of IBD student experience. Conclusions: Although students with IBD can demonstrate resilience and adaptive behavior, the evidence suggests there are significant limitations impacting their perceived experience. The barriers IBD students face impact their ability to experience postsecondary education as they intend to, forcing them to adjust in adaptive or maladaptive manners. This review also attempts to generate possible solutions to specific barriers identified from current research, generating directions of action for students, physicians, and academic supports.

National Infant Screening for Hearing Program in India: Necessity, Significance and Justification.

Hearing impairment is one of the most prevalent disorder in children and adults worldwide, which not only interferes with the acquisition, development and maintenance of speech and language skills but also adversely deprive the auditory nervous system for future learning. It can have long term harmful effect on educational, social, emotional and cognitive skills in young children; restrict the vocational options and employment opportunities in adults; and can cause isolation, loneliness and depression in older adults, if remain undetected and intervened at the earliest. However, early identification and intervention is known to greatly reverse the ill effects and improve the quality of life of children and adults with hearing impairment. Current clinical means and methods to identify and intervene hearing loss are convenient, cost effective, reasonably accurate beneficial and evidenced based, can be easily employed nation-wide for early identification and intervention of hearing loss. This paper attempts to convince medical colleagues, public health care experts and policy makers by justifying the hearing, as public health issue and relevance of medical screening criteria for hearing. It also discusses the preferred model of hearing screening and intervention strategies in India.

Virtual Dissection: An Interactive Anatomy Learning Tool.

The novelty of three-dimensional visualization technology (3DVT), such as virtual reality (VR), has captured the interest of many educational institutions. This study's objectives were to (1) assess how VR and physical models impact anatomy learning, (2) determine the effect of visuospatial ability on anatomy learning from VR and physical models, and (3) evaluate the impact of a VR familiarization phase on learning. This within-subjects, crossover study recruited 78 undergraduate students who studied anatomical structures at both physical and VR models and were tested on their knowledge immediately and 48 hours after learning. There were no significant differences in test scores between the two modalities on both testing days. After grouping participants on visuospatial ability, low visuospatial ability learners performed significantly worse on anatomy knowledge tests compared to their high visuospatial ability counterparts when learning from VR immediately (P = 0.001, d = 1.515) and over the long-term (P = 0.003, d = 1.279). In contrast, both low and high visuospatial ability groups performed similarly well when learning from the physical model and tested immediately after learning (P = 0.067) and over the long-term (P = 0.107). These results differ from current literature which indicates that learners with low visuospatial ability are aided by 3DVT. Familiarizing participants with VR before the learning phase had no impact on learning (P = 0.967). This study demonstrated that VR may be detrimental to low visuospatial ability students, whereas physical models may allow all students, regardless of their visuospatial abilities, to learn similarly well.

Gated and near-surface diffusion of charged fullerenes in nanochannels.

Nanoparticles and their derivatives have engendered significant recent interest. Despite considerable advances in nanofluidic physics, control over nanoparticle diffusive transport, requisite for a host of innovative applications, has yet to be demonstrated. In this study, we performed diffusion experiments for negatively and positively charged fullerene derivatives (dendritic fullerene-1, DF-1, and amino fullerene, AC60) in 5.7 and 13 nm silicon nanochannels in solutions with different ionic strengths. With DF-1, we demonstrated a gated diffusion whereby precise and reproducible control of the dynamics of the release profile was achieved by tuning the gradient of the ionic strength within the nanochannels. With AC60, we observed a near-surface diffusive transport that produced release rates that were independent of the size of the nanochannels within the range of our experiments. Finally, through theoretical analysis we were able to elucidate the relative importance of physical nanoconfinement, electrostatic interactions, and ionic strength heterogeneity with respect to these gated and near-surface diffusive transport phenomena. These results are significant for multiple applications, including the controlled administration of targeted nanovectors for therapeutics.

Device for rapid and agile measurement of diffusivity in micro- and nanochannels.

The lack of a viable theory for describing diffusivity when fluids are confined at the micro- and nanoscale [Ladero et al. Chem. Eng. Sci.2007, 62, 666-678; Deen AIChE J.1987, 33, 1409-1425] has necessitated accurate measurement of diffusivity (D) [Jin and Chen Chromatographia2000, 52, 17-21; Nie et al. Science1994, 266, 1018-1021; Durand et al. Anal. Chem.2009, 81, 5407-5412], crucial for a host of micro- and nanofluidic technologies [Grattoni et al. Curr. Pharm. Biotechnol.2010, 11, 343-365]. We demonstrate a rapid and agile method for the direct measurement of diffusivity in a system possessing 10(4) to 10(5) precisely fabricated channels with characteristic sizes (ß) ranging from micro- to nanometers. Custom chambers allowed us to measure the diffusivity in a closed unperturbed system using UV/vis spectroscopy. D was measured for rhodamine B (RhoB) in aqueous solution in channels of 200 and 1 µm, as well as 13 and 5.7 nm. The observed logarithmic scaling of diffusivity with ß, in close agreement with prior experiments, but far from theoretical prediction, surprisingly highlights that diffusivity is significantly altered even at the microscale. Accurate measurement of D by reducing the size of the source reservoir by 3 orders of magnitude (from 150 µL to 910 nL) proves that a substantial reduction in measurement time (from 7 days to 40 min) can be achieved. Our design thus is ready for rapid translation into a standard analytical tool--useful for multiple applications.

Nanochannel technology for constant delivery of chemotherapeutics: beyond metronomic administration.

PURPOSE: The purpose of this study is to demonstrate the long-term, controlled, zero-order release of low- and high-molecular weight chemotherapeutics through nanochannel membranes by exploiting the molecule-to-surface interactions presented by nanoconfinement. METHODS: Silicon membranes were produced with nanochannels of 5, 13 and 20 nm using standardized industrial microfabrication techniques. The study of the diffusion kinetics of interferon α-2b and leuprolide was performed by employing UV diffusion chambers. The released amount in the sink reservoir was monitored by UV absorbance. RESULTS: Continuous zero-order release was demonstrated for interferon α-2b and leuprolide at release rates of 20 and 100 µg/day, respectively. The release rates exhibited by these membranes were verified to be in ranges suitable for human therapeutic applications. CONCLUSIONS: Our membranes potentially represent a viable nanotechnological approach for the controlled administration of chemotherapeutics intended to improve the therapeutic efficacy of treatment and reduce many of the side effects associated with conventional drug administration.

A robust nanofluidic membrane with tunable zero-order release for implantable dose specific drug delivery.

This manuscript demonstrates a mechanically robust implantable nanofluidic membrane capable of tunable long-term zero-order release of therapeutic agents in ranges relevant for clinical applications. The membrane, with nanochannels as small as 5 nm, allows for the independent control of both dosage and mechanical strength through the integration of high-density short nanochannels parallel to the membrane surface with perpendicular micro- and macrochannels for interfacing with the ambient solutions. These nanofluidic membranes are created using precision silicon fabrication techniques on silicon-on-insulator substrates enabling exquisite control over the monodispersed nanochannel dimensions and surface roughness. Zero-order release of analytes is achieved by exploiting molecule to surface interactions which dominate diffusive transport when fluids are confined to the nanoscale. In this study we investigate the nanofluidic membrane performance using custom diffusion and gas testing apparatuses to quantify molecular release rate and process uniformity as well as mechanical strength using a gas based burst test. The kinetics of the constrained zero-order release is probed with molecules presenting a range of sizes, charge states, and structural conformations. Finally, an optimal ratio of the molecular hydrodynamic diameter to the nanochannel dimension is determined to assure zero-order release for each tested molecule.